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    Home / Computational » Machine Learning » This Post  
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    Classification: ROC Curve and AUC  |  Machine Learning Crash Course
  • admin
  • 233 days ago
  • Machine Learning
  • developers.google.com

    AUC provides an aggregate measure of performance across all possible
    classification thresholds. One way of interpreting AUC is as the probability
    that the model ranks a random positive example more highly than a random
    negative example. For example, given the following examples, which are arranged
    from left to right in ascending order of logistic regression predictions:

    • #Classification: ROC Curve and AUC
    •  0

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    • quite interesting article!
    • https://www.youtube.com/watch?v=dqgpkHe1pdw
    • https://www.youtube.com/watch?v=jx3g66DuY2I
    • https://www.youtube.com/watch?v=vOWnY1JDhJs
    • https://www.youtube.com/watch?v=87YngedYHFM
    • https://www.youtube.com/watch?v=5F-5zlDyt1k&feature=emb_title
    • https://www.youtube.com/watch?v=7Sb932i27UI
    • quite original study on biological psychiatry.
    • I think it is important to emphasize that TD is still common.
    • it seems interesting and fresh article on tardive dyskinesia.

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